Cloud engineer

We are seeking a highly skilled Cloud Engineer to architect, engineer, and optimize our enterprise-level, petabyte-scale data infrastructure. In this role, you will be pivotal in translating raw, heterogeneous data into governed, low-latency, and actionable data products. You will own the end-to-end data lifecycle from ingestion and streaming to transformation and delivery ensuring data quality, semantic consistency, and metadata integrity. You will partner with cross-functional teams to advance the bank’s data-driven strategy by building scalable, fault-tolerant solutions that empower advanced analytics and machine learning.

Key Responsibilities: Data Pipeline Development: Architect and maintain robust data pipelines using Ab Initio, Python, Scala, Apache Spark, and Microsoft Fabric/Databricks for ingestion and transformation Platform Management: Manage hybrid cloud platforms (Azure/Microsoft Fabric/SAS) and on-premises technologies (DB2, Netezza, Denodo), utilizing Infrastructure as Code (Ia C) principles Data Governance & Quality: Embed "data quality as code" by implementing automated validation, reconciliation, and auditing frameworks; manage technical metadata and lineage via the enterprise hub Security & Compliance: Partner with CISO and Data Governance teams to enforce security policies, including data masking and anonymization, ensuring strict adherence to privacy regulations (e.g., POPIA) Cross-Functional Collaboration: Serve as a technical partner to Data Scientists and Business Analysts to translate business requirements into scalable, secure data solutions Operational Excellence: Provide L2/L3 support for complex data incidents, ensuring minimal mean time to resolution and continuous optimization of data workflows through Data Ops practices Required Skills and Qualifications: Education: Undergraduate Degree in a relevant field (Computer Science, Engineering, or IT Experience: 2–5 years of professional experience in an IT or BI environment, with basic experience coordinating the work of others Technical Expertise: Cloud Platforms: Deep expertise in Azure (Data Factory, Microsoft Fabric, Databricks Programming: Proficiency in Python, Py Spark, and SQL Dev Ops/Data Ops: Strong experience with CI/CD pipelines, orchestration tools, and Infrastructure as Code Data Lifecycle: Competence in data conversion, profiling, and metadata management Soft Skills: Tech Savvy: Ability to adopt and experiment with emerging technologies Complex Problem Solving: Ability to distill complex, high-volume information into actionable insights Communication: Highly effective at collaborating with diverse stakeholders and creating clear, compelling technical documentation Preferred Qualifications: Experience with legacy or hybrid data environments such as Netezza, DB2, or Denodo Professional certification in Azure Data Engineering or Cloud Architecture Experience in the financial services sector, specifically dealing with regulated data environment